Hello statalist,
I am conducting a CHAID model to examine potential interaction of several
categorical variables in explaining variance in a dependent variable. CHAID
models do not have the capability of forcing covariates into the model,
i.e., examining the effect of the predictors on the dependent after
controlling for the effect of the covariate(s). To get around this
limitation, I want to perform a regression analysis of the same dependent
variable with the covariate as the sole predictor, then use the dependent
variable partialling out the effect of the covariate (call it y prime) as
the target variable in the CHAID model. Would y prime be the value predicted
by the regression model? What I'm struggling with is that if the
relationship between the dependent and the covariate is 0, the values
predicted from the regression will bear no resemblance to the original
dependent variable. What I want instead is the dependent variable with the
effect of the covariate partialled out; if the covariate has no relationship
to the dependent, then, in effect, nothing should be partialled out, i.e..,
y prime = y. Is it possible to do this?
Barth
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